Doo-Ahn Kwak

778 total citations
31 papers, 617 citations indexed

About

Doo-Ahn Kwak is a scholar working on Environmental Engineering, Nature and Landscape Conservation and Ecology. According to data from OpenAlex, Doo-Ahn Kwak has authored 31 papers receiving a total of 617 indexed citations (citations by other indexed papers that have themselves been cited), including 21 papers in Environmental Engineering, 16 papers in Nature and Landscape Conservation and 12 papers in Ecology. Recurrent topics in Doo-Ahn Kwak's work include Remote Sensing and LiDAR Applications (21 papers), Forest ecology and management (16 papers) and Remote Sensing in Agriculture (12 papers). Doo-Ahn Kwak is often cited by papers focused on Remote Sensing and LiDAR Applications (21 papers), Forest ecology and management (16 papers) and Remote Sensing in Agriculture (12 papers). Doo-Ahn Kwak collaborates with scholars based in South Korea, United States and India. Doo-Ahn Kwak's co-authors include Woo‐Kyun Lee, Jun‐Hak Lee, Greg S. Biging, Peng Gong, So Ra Kim, Taejin Park, M. Kafatos, Yowhan Son, A. K. Prasad and Hesham El‐Askary and has published in prestigious journals such as Sensors, International Journal of Remote Sensing and Remote Sensing.

In The Last Decade

Doo-Ahn Kwak

31 papers receiving 569 citations

Peers — A (Enhanced Table)

Peers by citation overlap · career bar shows stage (early→late) cites · hero ref

Name h Career Trend Papers Cites
Doo-Ahn Kwak South Korea 12 455 324 278 191 138 31 617
Masato Katoh Japan 12 390 0.9× 199 0.6× 256 0.9× 132 0.7× 117 0.8× 34 545
Udayalakshmi Vepakomma Canada 11 401 0.9× 243 0.8× 252 0.9× 189 1.0× 160 1.2× 15 535
Tomáš Bucha Slovakia 16 232 0.5× 213 0.7× 227 0.8× 233 1.2× 132 1.0× 37 553
Paweł Hawryło Poland 13 312 0.7× 203 0.6× 281 1.0× 225 1.2× 65 0.5× 43 552
Petra Adler Germany 13 309 0.7× 199 0.6× 236 0.8× 120 0.6× 144 1.0× 19 459
Ivan Balenović Croatia 14 378 0.8× 174 0.5× 200 0.7× 114 0.6× 119 0.9× 43 525
Azadeh Abdollahnejad Czechia 13 488 1.1× 169 0.5× 378 1.4× 151 0.8× 136 1.0× 17 638
She Guang-hui China 12 503 1.1× 330 1.0× 300 1.1× 149 0.8× 147 1.1× 33 653
Benjamin Kötz Switzerland 5 761 1.7× 418 1.3× 583 2.1× 293 1.5× 157 1.1× 8 900
Manuela Hirschmugl Austria 12 710 1.6× 348 1.1× 484 1.7× 283 1.5× 228 1.7× 29 924

Countries citing papers authored by Doo-Ahn Kwak

Since Specialization
Citations

This map shows the geographic impact of Doo-Ahn Kwak's research. It shows the number of citations coming from papers published by authors working in each country. You can also color the map by specialization and compare the number of citations received by Doo-Ahn Kwak with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Doo-Ahn Kwak more than expected).

Fields of papers citing papers by Doo-Ahn Kwak

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Doo-Ahn Kwak. Nodes represent research fields, and links connect fields that are likely to share authors. Colored nodes show fields that tend to cite the papers produced by Doo-Ahn Kwak. The network helps show where Doo-Ahn Kwak may publish in the future.

Co-authorship network of co-authors of Doo-Ahn Kwak

This figure shows the co-authorship network connecting the top 25 collaborators of Doo-Ahn Kwak. A scholar is included among the top collaborators of Doo-Ahn Kwak based on the total number of citations received by their joint publications. Widths of edges represent the number of papers authors have co-authored together. Node borders signify the number of papers an author published with Doo-Ahn Kwak. Doo-Ahn Kwak is excluded from the visualization to improve readability, since they are connected to all nodes in the network.

All Works

20 of 20 papers shown
1.
Kwak, Doo-Ahn. (2020). Change Prediction of Forestland Area in South Korea using Multinomial Logistic Regression Model. Journal of the Korean Association of Geographic Information Studies. 23(4). 42–51. 2 indexed citations
2.
Kwak, Doo-Ahn, et al.. (2018). Study on Applicability of Slope Types to Permission Standard for Forestland Use Conversion. Journal of the Korean Association of Geographic Information Studies. 21(4). 145–157. 1 indexed citations
3.
Lee, Woo‐Kyun, et al.. (2015). Spatio-temporal change in forest cover and carbon storage considering actual and potential forest cover in South Korea. Science China Life Sciences. 58(7). 713–723. 21 indexed citations
4.
Kwak, Doo-Ahn, et al.. (2015). Estimation of Stand-level Above Ground Biomass in Intact Tropical Rain Forests of Brunei using Airborne LiDAR data. Korean Journal of Remote Sensing. 31(2). 127–136. 1 indexed citations
5.
Kwak, Doo-Ahn, et al.. (2014). Estimating plot volume using lidar height and intensity distributional parameters. International Journal of Remote Sensing. 35(13). 4601–4629. 16 indexed citations
6.
Kwak, Doo-Ahn, Han Deok Kwak, Taehyun Park, et al.. (2013). Radial growth response of Pinus densiflora and Quercus spp. to topographic and climatic factors in South Korea. Journal of Plant Ecology. 6(5). 380–392. 41 indexed citations
7.
Park, Taejin, et al.. (2013). Unconstrained approach for isolating individual trees using high-resolution aerial imagery. International Journal of Remote Sensing. 35(1). 89–114. 5 indexed citations
8.
Son, Yowhan, et al.. (2013). Estimating carbon stocks in Korean forests between 2010 and 2110: a prediction based on forest volume–age relationships. Forest Science and Technology. 9(2). 105–110. 6 indexed citations
9.
Lee, Woo‐Kyun, Weihong Zhu, Jongyeol Lee, et al.. (2012). Vegetation Classification and Biomass Estimation using IKONOS Imagery in Mt. ChangBai Mountain Area. Journal of Korean Society of Forest Science. 101(3). 356–364. 2 indexed citations
10.
Park, Taejin, et al.. (2012). Maximum Canopy Height Estimation Using ICESat GLAS Laser Altimetry. Korean Journal of Remote Sensing. 28(3). 307–318. 1 indexed citations
11.
Park, Taejin, et al.. (2012). Study on Site Selection of A/R CDM Using LiDAR Data. Korean Journal of Remote Sensing. 28(5). 587–596. 1 indexed citations
12.
Kim, Moon Il, et al.. (2011). Early Detecting Damaged Trees by Pine Wilt Disease Using DI(Detection Index) from Portable Near Infrared Camera. Journal of Korean Society of Forest Science. 100(3). 374–381. 9 indexed citations
13.
Kim, So Ra, Woo‐Kyun Lee, Doo-Ahn Kwak, et al.. (2011). Forest Cover Classification by Optimal Segmentation of High Resolution Satellite Imagery. Sensors. 11(2). 1943–1958. 51 indexed citations
14.
Lee, Woo‐Kyun, et al.. (2011). Mapping forest functions using GIS in Selenge Province, Mongolia. Forest Science and Technology. 7(1). 23–29. 1 indexed citations
15.
Kwak, Doo-Ahn, et al.. (2010). Estimating stem volume and biomass of Pinus koraiensis using LiDAR data. Journal of Plant Research. 123(4). 421–432. 49 indexed citations
16.
Kwak, Doo-Ahn, et al.. (2010). Estimation of carbon storage based on individual tree detection in Pinus densiflora stands using a fusion of aerial photography and LiDAR data. Science China Life Sciences. 53(7). 885–897. 18 indexed citations
17.
Kwak, Doo-Ahn, et al.. (2010). Estimation of effective plant area index for South Korean forests using LiDAR system. Science China Life Sciences. 53(7). 898–908. 3 indexed citations
18.
Kwak, Doo-Ahn, et al.. (2010). Evaluation for Damaged Degree of Vegetation by Forest Fire using Lidar and a Digital Aerial Photograph. Photogrammetric Engineering & Remote Sensing. 76(3). 277–287. 9 indexed citations
19.
Kwak, Doo-Ahn, et al.. (2008). Estimation of effective plant area index using LiDAR data in forest of South Korea.. 237–246. 6 indexed citations
20.
Lee, Woo‐Kyun, et al.. (2006). GIS Application for Evaluating Forest Recreation Functions. Journal of the Korean Association of Geographic Information Studies. 9(1). 13–19. 2 indexed citations

Rankless uses publication and citation data sourced from OpenAlex, an open and comprehensive bibliographic database. While OpenAlex provides broad and valuable coverage of the global research landscape, it—like all bibliographic datasets—has inherent limitations. These include incomplete records, variations in author disambiguation, differences in journal indexing, and delays in data updates. As a result, some metrics and network relationships displayed in Rankless may not fully capture the entirety of a scholar's output or impact.

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